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Decentralized control with cross-coupled sensory feedback between body and limbs in sprawling locomotion

机译:分散控制在庞大的机器人中的身体和肢体之间的交叉耦合感官反馈

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Quadrupeds achieve rapid and highly adaptive locomotion owing to the coordination between their legs and other body parts such as their trunk, head, and tail, i.e. body-limb coordination. Therefore, a better understanding of the mechanism underlying body-limb coordination could provide informative insights into the improvement of legged robot mobility. Sprawling locomotion is a walking gait with lateral bending exhibited in primitive legged vertebrates such as salamanders and newts. Because primitive animals are anticipated to possess the essence of quadruped motor control, their locomotion helps better understand body-limb coordination mechanisms. Previous studies modeled neural networks in salamanders and employed it to control robots and investigate and emulate sprawling locomotion. However, these models predefined the relationship between the legs and the trunk, such that how body-limb coordination is attained is largely unknown. In this article, we demonstrate that sensory feedback facilitates body-limb coordination in sprawling locomotion and improves mobility through mathematical modeling and robot simulations. Our proposed model has cross-coupled sensory feedback, that is, bidirectional feedback from body to limb and limb to body, which leads to an appropriate relationship between the legs and the trunk without any predefined relationship. Resulting gaits are similar to the sprawling locomotion of salamanders and achieve high speed and energy efficiency that are at the same level as those of a neural network model, such as conventional models, optimizing the relationship between the legs and the trunk. Furthermore, sensory feedback contributes to the adaptability toward leg failure, and the bidirectionality of feedback facilitates parameter tuning for stable locomotion. These results suggest that cross-coupled sensory feedback facilitates sprawling locomotion and potentially plays an important role in the body-limb coordination mechanism.
机译:由于其腿部和其他身体部位(例如其躯干,头部和尾部)之间的协调,Quadrupeds实现了快速和高度自适应的运动。因此,更好地了解潜在的身体肢体协调机制可以为腿机器人移动性的改进提供信息丰富的见解。庞大的机器人是一种步行步态,横向弯曲在原始的腿脊椎动物如蝾螈和蝾螈中展出。由于预计原始动物拥有四足电机控制的本质,他们的机会有助于更好地理解身体肢体的协调机制。以前的研究在蝾螈中建模了神经网络,并采用它来控制机器人并调查和模拟蔓延的运动。然而,这些模型预定义了腿部和行李箱之间的关系,使得达到身体 - 肢体协调的关系在很大程度上是未知数。在本文中,我们证明了感觉反馈通过数学建模和机器人模拟来提高流动性,从而促进体内肢体协调。我们所提出的模型具有交叉耦合的感官反馈,即,从身体到肢体和肢体的双向反馈,这导致腿和躯干之间的适当关系而没有任何预定义的关系。产生的Gaits类似于蝾螈的倾斜运动,并实现与神经网络模型等相同水平的高速和能效,例如传统模型,优化腿部和躯干之间的关系。此外,感官反馈有助于对腿部故障的适应性,并且反馈的双向性有助于参数调整以进行稳定的运动。这些结果表明,交叉耦合的感觉反馈有利于倾斜的运动,并且可能在体肢协调机制中发挥重要作用。

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